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Collections including paper arxiv:2310.18356

LoRA Variant Catalogue

about 1 month ago

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Paper • 2403.14608 • Published Mar 21, 2024
Towards Better Parameter-Efficient Fine-Tuning for Large Language Models: A Position Paper

Paper • 2311.13126 • Published Nov 22, 2023 • 1
Comparing Retrieval-Augmentation and Parameter-Efficient Fine-Tuning for Privacy-Preserving Personalization of Large Language Models

Paper • 2409.09510 • Published Sep 14, 2024
Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning

Paper • 2407.01320 • Published Jul 1, 2024

HensonResearchFor1BitLLMs

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 628
Atom: Low-bit Quantization for Efficient and Accurate LLM Serving

Paper • 2310.19102 • Published Oct 29, 2023 • 11
AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning

Paper • 2311.00257 • Published Nov 1, 2023 • 10
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 50

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 153
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17, 2024 • 32
Tuning Language Models by Proxy

Paper • 2401.08565 • Published Jan 16, 2024 • 22
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10, 2024 • 69

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24

Papers: Pruning

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LoRAPrune: Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Paper • 2305.18403 • Published May 28, 2023 • 3
Parameter-Efficient Fine-Tuning with Layer Pruning on Free-Text Sequence-to-Sequence Modeling

Paper • 2305.08285 • Published May 15, 2023 • 1
A Comparative Analysis of Task-Agnostic Distillation Methods for Compressing Transformer Language Models

Paper • 2310.08797 • Published Oct 13, 2023 • 1

A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings

Paper • 2504.15610 • Published Apr 22, 2025 • 1
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models

Paper • 2502.13533 • Published Feb 19, 2025 • 13
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models

Paper • 2403.08822 • Published Feb 28, 2024
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?

Paper • 2407.18242 • Published Jul 25, 2024

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 109
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 43
BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15, 2024 • 21
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Paper • 2402.09727 • Published Feb 15, 2024 • 38

😱 Microsoft Papers with no code/data release

Collection of Microsoft Papers with no code/data release

MEGA: Multilingual Evaluation of Generative AI

Paper • 2303.12528 • Published Mar 22, 2023
MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks

Paper • 2311.07463 • Published Nov 13, 2023 • 15
Kosmos-2.5: A Multimodal Literate Model

Paper • 2309.11419 • Published Sep 20, 2023 • 56
A Unified View of Masked Image Modeling

Paper • 2210.10615 • Published Oct 19, 2022

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning

Paper • 2401.01325 • Published Jan 2, 2024 • 27
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Paper • 2401.02954 • Published Jan 5, 2024 • 55

Papers related to parameter efficient finetuning methods.

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 29
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 46

LoRA Variant Catalogue

about 1 month ago

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Paper • 2403.14608 • Published Mar 21, 2024
Towards Better Parameter-Efficient Fine-Tuning for Large Language Models: A Position Paper

Paper • 2311.13126 • Published Nov 22, 2023 • 1
Comparing Retrieval-Augmentation and Parameter-Efficient Fine-Tuning for Privacy-Preserving Personalization of Large Language Models

Paper • 2409.09510 • Published Sep 14, 2024
Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning

Paper • 2407.01320 • Published Jul 1, 2024

A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings

Paper • 2504.15610 • Published Apr 22, 2025 • 1
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models

Paper • 2502.13533 • Published Feb 19, 2025 • 13
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models

Paper • 2403.08822 • Published Feb 28, 2024
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?

Paper • 2407.18242 • Published Jul 25, 2024

HensonResearchFor1BitLLMs

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 628
Atom: Low-bit Quantization for Efficient and Accurate LLM Serving

Paper • 2310.19102 • Published Oct 29, 2023 • 11
AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning

Paper • 2311.00257 • Published Nov 1, 2023 • 10
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 50

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 109
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 43
BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15, 2024 • 21
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Paper • 2402.09727 • Published Feb 15, 2024 • 38

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 153
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17, 2024 • 32
Tuning Language Models by Proxy

Paper • 2401.08565 • Published Jan 16, 2024 • 22
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10, 2024 • 69

😱 Microsoft Papers with no code/data release

Collection of Microsoft Papers with no code/data release

MEGA: Multilingual Evaluation of Generative AI

Paper • 2303.12528 • Published Mar 22, 2023
MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks

Paper • 2311.07463 • Published Nov 13, 2023 • 15
Kosmos-2.5: A Multimodal Literate Model

Paper • 2309.11419 • Published Sep 20, 2023 • 56
A Unified View of Masked Image Modeling

Paper • 2210.10615 • Published Oct 19, 2022

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning

Paper • 2401.01325 • Published Jan 2, 2024 • 27
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Paper • 2401.02954 • Published Jan 5, 2024 • 55

Papers: Pruning

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LoRAPrune: Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Paper • 2305.18403 • Published May 28, 2023 • 3
Parameter-Efficient Fine-Tuning with Layer Pruning on Free-Text Sequence-to-Sequence Modeling

Paper • 2305.08285 • Published May 15, 2023 • 1
A Comparative Analysis of Task-Agnostic Distillation Methods for Compressing Transformer Language Models

Paper • 2310.08797 • Published Oct 13, 2023 • 1

Papers related to parameter efficient finetuning methods.

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 29
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 46

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